Predictive modeling the free hydraulic jumps pressure through advanced statistical methods

Detalhes bibliográficos
Autor(a) principal: Mousavi, Seyed Nasrollah
Data de Publicação: 2020
Outros Autores: Teixeira, Eder Daniel, Steinke Júnior, Renato, Bocchiola, Daniele, Nabipour, Narjes, Mosavi, Amir, Shamshirband, Shahabodin
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/217152
Resumo: Pressure fluctuations beneath hydraulic jumps potentially endanger the stability of stilling basins. This paper deals with the mathematical modeling of the results of laboratory-scale experiments to estimate the extreme pressures. Experiments were carried out on a smooth stilling basin underneath free hydraulic jumps downstream of an Ogee spillway. From the probability distribution of measured instantaneous pressures, pressures with different probabilities could be determined. It was verified that maximum pressure fluctuations, and the negative pressures, are located at the positions near the spillway toe. Also, minimum pressure fluctuations are located at the downstream of hydraulic jumps. It was possible to assess the cumulative curves of pressure data related to the characteristic points along the basin, and different Froude numbers. To benchmark the results, the dimensionless forms of statistical parameters include mean pressures (P*m), the standard deviations of pressure fluctuations (_*X), pressures with different non-exceedance probabilities (P*k%), and the statistical coefficient of the probability distribution (Nk%) were assessed. It was found that an existing method can be used to interpret the present data, and pressure distribution in similar conditions, by using a new second-order fractional relationships for _*X, and Nk%. The values of the Nk% coefficient indicated a single mean value for each probability.
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spelling Mousavi, Seyed NasrollahTeixeira, Eder DanielSteinke Júnior, RenatoBocchiola, DanieleNabipour, NarjesMosavi, AmirShamshirband, Shahabodin2021-01-08T04:06:48Z20202227-7390http://hdl.handle.net/10183/217152001115119Pressure fluctuations beneath hydraulic jumps potentially endanger the stability of stilling basins. This paper deals with the mathematical modeling of the results of laboratory-scale experiments to estimate the extreme pressures. Experiments were carried out on a smooth stilling basin underneath free hydraulic jumps downstream of an Ogee spillway. From the probability distribution of measured instantaneous pressures, pressures with different probabilities could be determined. It was verified that maximum pressure fluctuations, and the negative pressures, are located at the positions near the spillway toe. Also, minimum pressure fluctuations are located at the downstream of hydraulic jumps. It was possible to assess the cumulative curves of pressure data related to the characteristic points along the basin, and different Froude numbers. To benchmark the results, the dimensionless forms of statistical parameters include mean pressures (P*m), the standard deviations of pressure fluctuations (_*X), pressures with different non-exceedance probabilities (P*k%), and the statistical coefficient of the probability distribution (Nk%) were assessed. It was found that an existing method can be used to interpret the present data, and pressure distribution in similar conditions, by using a new second-order fractional relationships for _*X, and Nk%. The values of the Nk% coefficient indicated a single mean value for each probability.application/pdfengMathematics. Basel: MDPI. Vol. 8, n. 3 (mar. 2020), 323, 16 p.Ressalto hidraulicoModelagem matemáticaFlutuações de pressãoModelos físicosVertedouroDistribuicao de probabilidadesMathematical modelingExtreme pressureHydraulic jumpStilling basinDeviation of pressure fluctuationsStatistical coefficient of the probability distributionPredictive modeling the free hydraulic jumps pressure through advanced statistical methodsEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001115119.pdf.txt001115119.pdf.txtExtracted Texttext/plain56903http://www.lume.ufrgs.br/bitstream/10183/217152/2/001115119.pdf.txt4160434118165c7ca08bf135c5f4f338MD52ORIGINAL001115119.pdfTexto completo (inglês)application/pdf4519322http://www.lume.ufrgs.br/bitstream/10183/217152/1/001115119.pdfad430b516f15f2922c537ba774092b1fMD5110183/2171522023-12-29 04:22:46.563757oai:www.lume.ufrgs.br:10183/217152Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-12-29T06:22:46Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
title Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
spellingShingle Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
Mousavi, Seyed Nasrollah
Ressalto hidraulico
Modelagem matemática
Flutuações de pressão
Modelos físicos
Vertedouro
Distribuicao de probabilidades
Mathematical modeling
Extreme pressure
Hydraulic jump
Stilling basin
Deviation of pressure fluctuations
Statistical coefficient of the probability distribution
title_short Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
title_full Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
title_fullStr Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
title_full_unstemmed Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
title_sort Predictive modeling the free hydraulic jumps pressure through advanced statistical methods
author Mousavi, Seyed Nasrollah
author_facet Mousavi, Seyed Nasrollah
Teixeira, Eder Daniel
Steinke Júnior, Renato
Bocchiola, Daniele
Nabipour, Narjes
Mosavi, Amir
Shamshirband, Shahabodin
author_role author
author2 Teixeira, Eder Daniel
Steinke Júnior, Renato
Bocchiola, Daniele
Nabipour, Narjes
Mosavi, Amir
Shamshirband, Shahabodin
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Mousavi, Seyed Nasrollah
Teixeira, Eder Daniel
Steinke Júnior, Renato
Bocchiola, Daniele
Nabipour, Narjes
Mosavi, Amir
Shamshirband, Shahabodin
dc.subject.por.fl_str_mv Ressalto hidraulico
Modelagem matemática
Flutuações de pressão
Modelos físicos
Vertedouro
Distribuicao de probabilidades
topic Ressalto hidraulico
Modelagem matemática
Flutuações de pressão
Modelos físicos
Vertedouro
Distribuicao de probabilidades
Mathematical modeling
Extreme pressure
Hydraulic jump
Stilling basin
Deviation of pressure fluctuations
Statistical coefficient of the probability distribution
dc.subject.eng.fl_str_mv Mathematical modeling
Extreme pressure
Hydraulic jump
Stilling basin
Deviation of pressure fluctuations
Statistical coefficient of the probability distribution
description Pressure fluctuations beneath hydraulic jumps potentially endanger the stability of stilling basins. This paper deals with the mathematical modeling of the results of laboratory-scale experiments to estimate the extreme pressures. Experiments were carried out on a smooth stilling basin underneath free hydraulic jumps downstream of an Ogee spillway. From the probability distribution of measured instantaneous pressures, pressures with different probabilities could be determined. It was verified that maximum pressure fluctuations, and the negative pressures, are located at the positions near the spillway toe. Also, minimum pressure fluctuations are located at the downstream of hydraulic jumps. It was possible to assess the cumulative curves of pressure data related to the characteristic points along the basin, and different Froude numbers. To benchmark the results, the dimensionless forms of statistical parameters include mean pressures (P*m), the standard deviations of pressure fluctuations (_*X), pressures with different non-exceedance probabilities (P*k%), and the statistical coefficient of the probability distribution (Nk%) were assessed. It was found that an existing method can be used to interpret the present data, and pressure distribution in similar conditions, by using a new second-order fractional relationships for _*X, and Nk%. The values of the Nk% coefficient indicated a single mean value for each probability.
publishDate 2020
dc.date.issued.fl_str_mv 2020
dc.date.accessioned.fl_str_mv 2021-01-08T04:06:48Z
dc.type.driver.fl_str_mv Estrangeiro
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/217152
dc.identifier.issn.pt_BR.fl_str_mv 2227-7390
dc.identifier.nrb.pt_BR.fl_str_mv 001115119
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Mathematics. Basel: MDPI. Vol. 8, n. 3 (mar. 2020), 323, 16 p.
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRGS
instname:Universidade Federal do Rio Grande do Sul (UFRGS)
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instname_str Universidade Federal do Rio Grande do Sul (UFRGS)
instacron_str UFRGS
institution UFRGS
reponame_str Repositório Institucional da UFRGS
collection Repositório Institucional da UFRGS
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